Below is a list of some of the papers, with references to the code where available. Unfortunately, the code for many of the applications in the GAMP matlab package is not yet well-documented, although we hope to provide more details soon.

Uses the GAMP package for rank one matrix factorization. The paper shows that you can obtain an exact state evolution analysis for predicting the GAMP performance. In the future, we hope to extend this to higher ranks.

Extends the GAMP method to estimating vectors described by general graphical models. One example of the methodology is for group or structured sparsity which yields a computationally efficient and general procedure.

Uses an iterative version of GAMP for estimating neural connectivity and visual receptive field estimation of sensory neurons.

Code is in the directory gampmatlab\trunk\code\neural. However, some of the data is not included as it requires permission from Janelia Farms which conducted the neurological experiments. Please email Sundeep Rangan if you request access.